"A unified DB ingestion framework built on Change Data Capture (Debezium/TiCDC), Kafka, Flink, Spark, and Iceberg provides access to online database changes in minutes (not hours or days) while processing only changed records, resulting in significant infrastructure cost savings."
Pinterest's legacy batch-based data infrastructure suffered from high latency exceeding 24 hours, operational complexity, and inefficient resource utilization due to full-table batch jobs reprocessing unchanged records. The new framework addresses these limitations by implementing Change Data Capture technology integrated with Kafka, Flink, Spark, and Iceberg. The architecture separates CDC tables, which function as append-only ledgers recording changes with sub-five-minute latency, from base tables maintaining historical snapshots updated every 15 minutes to an hour. The solution supports multiple database types including MySQL, TiDB, and KVStore, operates through configuration-driven setup for simplified onboarding, and delivers at-least-once guarantees while significantly reducing infrastructure costs.
#database-ingestion #change-data-capture #real-time-data-processing #data-infrastructure #apache-iceberg
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